Fresh-frozen Samples Research Articles

A proteome-wide association study identifies putative causal proteins for breast cancer risk.

Genome-wide association studies (GWAS) have identified more than 200 breast cancer risk-associated genetic loci, yet the causal genes and biological mechanisms for most loci remain elusive. Proteins, as final gene products, are pivotal in cellular function. In this study, we conducted a proteome-wide association study (PWAS) to identify proteins in breast tissue related to breast cancer risk. We profiled the proteome in fresh frozen breast tissue samples from 120 cancer-free European-ancestry women from the Susan G. Komen Tissue Bank (KTB). Protein expression levels were log2-transformed then normalized via quantile and inverse-rank transformations. GWAS data were also generated for these 120 samples. These data were used to build statistical models to predict protein expression levels via cis-genetic variants using the elastic net method. The prediction models were then applied to the GWAS summary statistics data of 133,384 breast cancer cases and 113,789 controls to assess the associations of genetically predicted protein expression levels with breast cancer risk overall and its subtypes using the S-PrediXcan method. A total of 6388 proteins were detected in the normal breast tissue samples from 120 women with a high detection false discovery rate (FDR) p value < 0.01. Among the 5820 proteins detected in more than 80% of participants, prediction models were successfully built for 2060 proteins with R > 0.1 and P < 0.05. Among these 2060 proteins, five proteins were significantly associated with overall breast cancer risk at an FDR p value < 0.1. Among these five proteins, the corresponding genes for proteins COPG1, DCTN3, and DDX6 were located at least 1 Megabase away from the GWAS-identified breast cancer risk variants. COPG1 was associated with an increased risk of breast cancer with a p value of 8.54 × 10-4. Both DCTN3 and DDX6 were associated with a decreased risk of breast cancer with p values of 1.01 × 10-3 and 3.25 × 10-4, respectively. The corresponding genes for the remaining two proteins, LSP1 and DNAJA3, were located in previously GWAS-identified breast cancer risk loci. After adjusting for GWAS-identified risk variants, the association for DNAJA3 was still significant (p value of 9.15 × 10-5 and adjusted p value of 1.94 × 10-4). However, the significance for LSP1 became weaker with a p value of 0.62. Stratification analyses by breast cancer subtypes identified three proteins, SMARCC1, LSP1, and NCKAP1L, associated with luminal A, luminal B, and ER-positive breast cancer. NCKAP1L was located at least 1Mb away from the GWAS-identified breast cancer risk variants. After adjusting for GWAS-identified breast cancer risk variants, the association for protein LSP1 was still significant (adjusted p value of 6.43 × 10-3 for luminal B subtype). We conducted the first breast-tissue-based PWAS and identified seven proteins associated with breast cancer, including five proteins not previously implicated. These findings help improve our understanding of the underlying genetic mechanism of breast cancer development.

Evaluation of whole genome sequencing utility in identifying driver alterations in cancer genome

In cancer genome analysis, identifying pathogenic alterations and assessing their effects on oncogenic processes is important. Although whole exome sequencing (WES) can effectively detect such changes, driver alterations could not be identified in 27.8% of the cases, according to a previous study. The objectives of the present study were to evaluate the utility of whole genome sequencing (WGS) and clarify its differences with WES in terms of driver alteration detection. For this purpose, WGS analysis was conducted on 177 driverless WES samples, selected from 5,480 fresh frozen samples derived from 5,140 Japanese patients with cancer. These samples were selected as primary tumor, both WES and transcriptome profiling were performed, estimated tumor content of ≥ 30%, and no driver alterations were identified by WES. WGS identified driver and likely driver alterations in 68.4 and 22.6% of the samples, respectively. The most frequent alteration type was oncogene amplification, followed by tumor suppressor gene deletion and small variants located outside the coding region. In the remaining 9.0% of samples, no such signals were identified; therefore, further investigations are required. The current study clearly demonstrated the role and utility of WGS in identifying genomic alterations that contribute to tumorigenesis.

Single nucleus DNA sequencing of flow sorted archived frozen and formalin fixed paraffin embedded solid tumors.

Archived samples, including frozen and formalin fixed paraffin embedded (FFPE) tissues, are a vast resource of clinically annotated materials for the application of high-definition genomics to improve patient management and provide a molecular basis for the delivery of personalized cancer therapeutics. Notably, FFPE tissues are stable, provide repeat sampling of tissues of interest, and can be stored indefinitely at ambient temperature. The development of single cell DNA sequencing (scDNA-seq) technologies provides an unparalleled opportunity for the study of tumor heterogeneity and the identification of often rare subclonal cell populations that drive tumor evolution and progression to advanced therapy resistant disease. However, major limitations to the use of archived tissues for scDNA-seq include the low yields of intact cells in the presence of high levels of subcellular debris in biopsies, and the highly variable quantity and quality of the DNA extracted from samples of interest. The latter is of high significance for the use of FFPE tissues due to the presence of DNA-protein crosslinks. In addition, many samples, notably tumors arising in solid tissues, contain admixtures of reactive stroma, inflammatory cells, and necrosis in immediate contact with tumor cells. To expand their use for translational studies, we optimized flow sorting and sequencing of single nuclei from archived fresh frozen (FF) and FFPE tumor tissues. Our methods, which include isolation of intact nuclei suitable for library preparations, quality control (QC) metrics for each step, and a single cell sequencing bioinformatic processing and analysis pipeline, were validated with flow sorted nuclei from matching FF and FFPE ovarian cancer surgical samples and a sequencing panel of 553 amplicons targeting single nucleotide and copy number variants in genes of interest. Our flow sorting based protocol provides intact nuclei suitable for snDNA-seq from archival FF and FFPE tissues. Furthermore, we have developed QC steps that optimize the preparation and selection of samples for deep single cell clonal profiling. Our data processing pipeline captures rare subclones in tumors with highly variable genomes based on variants in genes of interest.

Proteogenomic Characterization of Early Intrahepatic Recurrence after Curative-Intent Treatment of Colorectal Liver Metastases.

Clinical and pathological factors are insufficient to accurately identify patients at risk of early recurrence after curative-intent treatment of colorectal liver metastases (CRLM). This study aimed to identify candidate prognostic proteogenomic biomarkers for early intrahepatic recurrence after curative-intent resection of CRLM. Patients diagnosed with intrahepatic recurrence within 6 months of liver resection were categorized as the "early recurrence" group, while those who achieved a recurrence-free status for 10 years were designated as "durable remission". Comprehensive genomic and proteomic profiling of fresh frozen samples from these prognostically distinct groups was performed using the TruSight Oncology 500 assay and label-free data-dependent acquisition liquid chromatography-mass spectrometry. Genetic alterations were identified in 117 of the 523 profiled genes in patients with early recurrence. The most common somatic mutations linked to early recurrence were TP53 (88%), APC (71%), KRAS (38%), and SMAD4 (21%). SMAD4 alterations were absent in samples from patients with a durable remission. Calponin-2, versican core protein, glutathione peroxidase 3, fibulin-5, and amyloid-β precursor protein were upregulated more than 2-fold in early recurrence. Exploratory analysis of these proteogenomic biomarkers suggests that SMAD4, calponin-2, and glutathione peroxidase 3 may have the potential to predict early recurrence, enabling improved prognostication and precision oncology in CRLM.

A-038 Interlaboratory Comparison of Parathyroid Hormone Analytical Results Across Clinical Assays from 8 Manufacturers - Steps Towards Standardization

Abstract Background Parathyroid hormone (PTH) is an 84 amino acid peptide produced by the parathyroid gland and is a key biomarker used for the diagnosis and treatment of Chronic Kidney Disease-Mineral and Bone Disorder, as well as hypo- and hyperparathyroidism. PTH clinical assays were previously reported to exhibit significant inter-assay measurement variability, which limits the utility of PTH as a diagnostic biomarker and can result in the misclassification of patients. Thus, there is a need for PTH clinical assay standardization to improve clinical assay measurement agreement. The Centers for Disease Control and Prevention’s Clinical Standardization Program (CDC-CSP) will launch a PTH standardization program, which is in support of and coordinated with the IFCC Committee on Bone Metabolism. In preparation, the CDC-CSP conducted an Inter-Laboratory Comparison Study to evaluate the current status of PTH inter-assay variability and to investigate potential sources of variability. Methods Eight PTH assay manufacturer’s laboratories measured PTH in 42 deidentified, fresh-frozen single donor serum samples in duplicate over 2 independent runs. Sample PTH concentrations ranged from 1.3 - 324 pg/mL, based on initial screening values. Five manufacturers submitted data for 2 different assays, resulting in PTH measurements from 13 assays total. Data were submitted to the CDC CSP for analysis. Results Assay precision was &amp;lt;5% for 10/13 measurement procedures (MP) assessed and 3 MPs exhibited precisions between 5 - 18%. Assay-specific PTH measurements demonstrated good linear correlation compared to the all-assay mean concentration. Interestingly, inter-assay variability increased with increasing PTH concentrations, with individual sample standard deviations increasing from 2.9 - 123, with a mean SD of 24.1 and individual sample CVs increasing from 18.9 - 44.5%, with a mean CV of 24.2%. Conclusions This study provides new insights into PTH inter-assay variability and assay performance for assays commonly used in the clinical setting. The findings of this PTH Interlaboratory Comparison Study establish a baseline for PTH inter-assay variability and will guide future PTH standardization efforts.

Phosphoproteomic subtyping of gastric cancer reveals dynamic transformation with chemotherapy and guides targeted cancer treatment

There are only a few effective molecular targeted agents for advanced unresectable or recurrent advanced gastric cancer (AGC), which has a poor prognosis with a median survival time of less than 14months. Focusing on phosphorylation signaling in cancer cells, we have been developing deep phosphoproteome analysis from minute endoscopic biopsy specimens frozen within 20s of collection. Phosphoproteomic analysis of 127 fresh-frozen endoscopic biopsy samples from untreated patients with AGC revealed three subtypes reflecting different cellular signaling statuses. Subsequent serial biopsy analysis has revealed the dynamic mesenchymal transitions within cancer cells, along with the concomitant rewiring of the kinome network, ultimately resulting in the conversion to the epithelial-mesenchymal transition (EMT) subtype throughout treatment. We present our investigation of intracellular signaling related to the EMT in gastric cancer and propose therapeutic approaches targeting AXL. This study also provides a wealth of resources for the future development of treatments and biomarkers for AGC.

IGFBP5 in osteosarcoma tumorigenesis: Gene expression profile among metastatic and non-metastatic patients

Osteosarcoma (OS) is the most frequent primary malignant bone tumor among children and adolescents, with a peak of incidence in the second decade of life. The presence of metastasis at diagnosis in OS patients significantly decreases the chances of survival and new therapy approaches are needed. The IGFBP5 gene is related to osteoblasts metabolism and some studies have pointed out a role of its low expressions in OS development and metastasis. In this study, we aimed to establish an IGFBP5 gene expression profile among metastatic and non-metastatic OS patients throughout the treatment and development of the disease. Fresh-frozen tumor samples were obtained from 40 patients admitted to treatment at the Pediatric Oncology Institute (IOP/GRAACC/UNIFESP) and divided by clinical status: metastatic or non-metastatic disease. For each patient, samples before and after chemotherapy treatment were obtained, as well as metastasis and lung tissue surrounding metastasis samples from the metastatic patients. A quantitative real-time PCR was used to investigate IGFBP5 expression. Our analyses demonstrate that non-metastatic patients presented lower IGFBP5 expression in their pre-chemotherapy samples compared with metastatic patients, suggesting that low expressions of this gene could help triggering the OS tumorigenesis but that its action alone is not sufficient to activate the metastatic process. Heterogeneity in IGFBP5 expressions within groups was also seen. We observed that IGFBP5 and two MAPK genes, a downstream pathway in the IGFBP5 axis, are differentially expressed in OS samples of non-metastatic patients. Further investigation about these genes’ modulations might lead to a better understanding of metastasis development in OS.

DICER1 Variants in Pediatric and Young Adult Thyroid Nodules.

Background: Recent studies have suggested that pathogenic variants of the DICER1 gene could be a driver of alterations in some pediatric thyroid nodules, but data are still limited. The aim of this study was to detect variants in the DICER1 gene in a large cohort of pediatric thyroid nodules and then correlate them with clinicopathological data, with a focus on the disease prognosis in patients with thyroid carcinoma. Methods: This retrospective cohort study consisted of 350 pediatric and young adult patients (aged 2-21 years) with thyroid nodules, from whom 275 fresh-frozen thyroid nodule samples and 92 fine-needle aspiration biopsy (FNAB) samples were collected. After an analysis of variants in major genetic alterations of thyroid tumors, variants in the DICER1 gene were identified using next-generation sequencing and multiplex ligation-dependent probe amplification methods. Peripheral blood was analyzed from patients with DICER1-positive tumors. The results of genetic analysis were then correlated with clinicopathological data. Results: Variants in the DICER1 gene were detected in a total of 24/350 (6.9%; 95%CI [4.4;10.0]) pediatric and young adult patients, respectively, in 10/119 (8.4%; [4.1;14.9]) patients with benign fresh-frozen tissue, in 8/141 (5.7%; [1.9;9.5]) with papillary thyroid carcinoma (PTC) and in 6/86 (7.0%; [4.1;14.6]) patients with FNAB. No other gene alteration was found in DICER1-positive samples. Germline DICER1 variants were identified in 11/24 (45.8%; [25.6;67.2]) patients. Two somatic (biallelic) variants in the DICER1 gene were found in 9/24 (37.5%; [18.8;59.4]) thyroid nodules. Somatic deletions of at least 3 Mbp long were revealed in 2/24 (8.3%; [1.0;27.0]) cases. DICER1-positive PTCs were significantly associated with the follicular subtype of PTC (p = 0.001), encapsulation (p = 0.006) and were larger in size (p = 0.035), but with no extrathyroidal extension (p = 0.039), and less frequent lymph node metastases (p = 0.003) compared with DICER1-negative PTCs. Patients with DICER1-positive PTC had an excellent response to treatment in 75% of cases. Conclusions: Variants of the DICER1 gene are frequently found in the thyroid nodules of pediatric and young adult patients. In our patients, DICER1-positive PTCs showed low invasiveness. Our findings support considering more conservative management for DICER1-positive low-risk PTCs.

Molecular classification of ovarian high-grade serous/endometrioid carcinomas through multi-omics analysis: JGOG3025-TR2 study.

Considerable interobserver variability exists in diagnosis of ovarian high-grade endometrioid carcinoma (HGEC) and high-grade serous carcinoma (HGSC) due to histopathological similarities. While homologous recombination deficiency (HRD) correlates with drug sensitivity in HGSC, the molecular features of HGEC are unclear. Fresh-frozen samples from 15 ovarian HGECs and 274 ovarian HGSCs in the JGOG-TR2 cohort were submitted to targeted DNA sequencing, RNA sequencing, DNA methylation array, and SNP array. We additionally analyzed 555 ovarian HGSCs from TCGA-OV and 287 endometrial high-grade carcinomas from TCGA-UCEC. Unsupervised clustering using copy number signatures identified four distinct tumor groups (C1, C2, C3 and C4). C1 (n = 41) showed CCNE1 amplification and poor survival. C2 (n = 160) and C3 (n = 59) showed high BRCA1/2 alteration frequency with low and moderate ploidy, respectively. C4 (n = 22) was characterized by favorable outcome, higher HGEC proportion, no BRCA1/2 alteration or CCNE1 amplification, and low levels of HRD score, ploidy, intra-tumoral heterogeneity, cell proliferation rate, and WT1 gene expression. Notably, C4 exhibited a normal endometrium-like DNA methylation profile, thus, defined as "HGEC-type" tumors, which were also identified in TCGA-OV and TCGA-UCEC. Ovarian "HGEC-type" tumors present a non-HRD status, favorable prognosis, and endometrial differentiation, possibly constituting a subset of clinically diagnosed HGSCs.

Systematic review and feasibility study on pre-analytical factors and genomic analyses on archival formalin-fixed paraffin-embedded breast cancer tissue

Formalin-fixed paraffin-embedded (FFPE) tissue represents a valuable source for translational cancer research. However, the widespread application of various downstream methods remains challenging. Here, we aimed to assess the feasibility of a genomic and gene expression analysis workflow using FFPE breast cancer (BC) tissue. We conducted a systematic literature review for the assessment of concordance between FFPE and fresh-frozen matched tissue samples derived from patients with BC for DNA and RNA downstream applications. The analytical performance of three different nucleic acid extraction kits on FFPE BC clinical samples was compared. We also applied a newly developed targeted DNA Next-Generation Sequencing (NGS) 370-gene panel and the nCounter BC360® platform on simultaneously extracted DNA and RNA, respectively, using FFPE tissue from a phase II clinical trial. Of the 3701 initial search results, 40 articles were included in the systematic review. High degree of concordance was observed in various downstream application platforms. Moreover, the performance of simultaneous DNA/RNA extraction kit was demonstrated with targeted DNA NGS and gene expression profiling. Exclusion of variants below 5% variant allele frequency was essential to overcome FFPE-induced artefacts. Targeted genomic analyses were feasible in simultaneously extracted DNA/RNA from FFPE material, providing insights for their implementation in clinical trials/cohorts.

Changes in tumor microbiome and underlying value according to response to neoadjuvan chemotherapy for in patients with gastric cancer

Objective: To investigate the relationship between efficacy of neoadjuvant chemotherapy (NACT) for gastric cancer and gastric microecology. Methods: This was a retrospective observational study using fresh frozen operative specimens. The specimens had been stored in the tumor sample bank of the Department of Gastrointestinal Surgery of the Affiliated Hospital of Qingdao University from January 2017 to January 2023 after having been collected from 31 patients with pathologically diagnosed gastric cancer who had no metastases and had received only neoadjuvant chemotherapy preoperatively. The study patients had all successfully undergone radical gastric cancer surgery. Patients with metastases or other primary tumor foci and/or had received other therapies within 1 month prior to surgery, including immunotherapy, targeted therapies and probiotics, were excluded. The tumors were graded and grouped in accordance with the 8th edition of the American Joint Committee on Cancer staging system and the Tumor Regression Grading System (TRG) of the College of American Pathologists. Those with TRG Grades 0-1, ypT0-1 and ypN0 were classified as responsive (Group R, 12 cases), whereas those with TRG Grades 2-3 and ypT2-4 or ypN+ were classified as non-responsive (Group NR, 19 cases). The fresh frozen samples were processed and analyzed using 16S rRNA sequencing. Alpha and beta diversity analyses were performed using the Q2-diversity plug-in for QIIME2 and STAMP was used to determine the default parameters and differentially enriched bacterial taxa in the two groups. High-dimensional class comparisons were performed by effect size linear discriminant analysis, and potential functional distributions of microbiomes were predicted using PICRUST2 (v2.3.0-b) software. Results: Groups R and NR did not differ significantly in sex, age, body mass index, smoking history, tumor location, cTNM stage before NACT, and neoadjuvant chemotherapy (all P>0.05), whereas tumor size and ypTNM stage after NACT differed significantly between the two groups (both P=0.001). Alpha and beta diversity analysis of the gastric microbiota did not reveal a statistically significant difference in alpha diversity between the two groups (P>0.05), whereas there was a statistically significant difference in beta diversity between the two groups (P=0.004). Four family-level bacterial taxa, namely Coriobacteriaceae, Ruminococcaceae, Veillonellaceae, and Lachnospiraceae, were enriched in the R group, whereas four bacterial taxa dominated by phylum Proteobacteria were enriched in the NR group. Metabolic pathways of various amino acids, including citric acid cycle and alanine, were found to be potentially predictive. Conclusions: There are significant differences in the abundance and composition of gastric microecology in gastric cancer patients with different responses to NACT.

Paired comparison of the analytical performance between the Oncomine™ Comprehensive Assay v3 and whole-exome sequencing of ovarian cancer tissue

BackgroundNext-generation sequencing (NGS) has been implemented in clinical oncology as a personalized medicine tool to identify targetable genetic alterations and to guide treatment decisions. However, the optimal NGS test strategy and target genes for clinical use are still being discussed. The aim was to compare the performance of the Oncomine™ Comprehensive Assay v3 (OCAv3) (targeted gene panel) and whole-exome sequencing (WES) to investigate somatic single and multiple nucleotide variants and small indels in ovarian cancer patients.Methods and resultsGenomic DNA was isolated from fresh frozen samples of five high-grade serous (HGSC) and three clear cell ovarian (oCCC) cancer patients. Exome sequencing libraries were prepared by using the Ion AmpliSeq Exome RDY kit, whereas libraries for OCAv3 were prepared using by Ion AmpliSeq™ Library Kit Plus. Sequencing was performed using the Ion S5XL System (Thermo Fisher Scientific). When including only variants classified as pathogenic, likely pathogenic or unknown significance based on ClinVar database verdicts and comparing overlapping regions covered both by the OCAv3 assay and WES, 23 variants were detected by both assays. However, OCAv3 detected additionally two variants: ARID1A: p.Gln563Ter and TP53: p.Ser261ValfsTer84 that have not passed WES filtering criteria due to low coverage.ConclusionsWith the present treatment possibilities, OCAv3 panel testing provided higher diagnostic yield due to better coverage. Our study emphasizes that WES, although offering the potential to identify novel findings in genes not covered by OCAv3, might overlook variants in genes relevant for OC.

Morphological and molecular preservation through universal preparation of fresh-frozen tissue samples for multimodal imaging workflows.

The landscape of tissue-based imaging modalities is constantly and rapidly evolving. While formalin-fixed, paraffin-embedded material is still useful for histological imaging, the fixation process irreversibly changes the molecular composition of the sample. Therefore, many imaging approaches require fresh-frozen material to get meaningful results. This is particularly true for molecular imaging techniques such as mass spectrometry imaging, which are widely used to probe the spatial arrangement of the tissue metabolome. As high-quality fresh-frozen tissues are limited in their availability, any sample preparation workflow they are subjected to needs to ensure morphological and molecular preservation of the tissues and be compatible with as many of the established and emerging imaging techniques as possible to obtain the maximum possible insights from the tissues. Here we describe a universal sample preparation workflow, from the initial step of freezing the tissues to the cold embedding in a new hydroxypropyl methylcellulose/polyvinylpyrrolidone-enriched hydrogel and the generation of thin tissue sections for analysis. Moreover, we highlight the optimized storage conditions that limit molecular and morphological degradation of the sections. The protocol is compatible with human and plant tissues and can be easily adapted for the preparation of alternative sample formats (e.g., three-dimensional cell cultures). The integrated workflow is universally compatible with histological tissue analysis, mass spectrometry imaging and imaging mass cytometry, as well as spatial proteomic, genomic and transcriptomic tissue analysis. The protocol can be completed within 4 h and requires minimal prior experience in the preparation of tissue samples for multimodal imaging experiments.

Abstract PS15-06: Results of the window-of-opportunity PIONEER trial evaluating addition of the progesterone receptor (PR) agonist megestrol to letrozole for early stage estrogen receptor (ER) positive breast cancer: exploiting ER-PR interaction

Abstract Background: Pre-clinical data suggest that combining anti-estrogen treatment with a progesterone receptor agonist leads to greater inhibition of tumor proliferation, due to molecular interactions between ER and PR [1]. A high dose of the PR agonist megestrol (160mg daily) is approved as monotherapy for the treatment of ER positive metastatic breast cancer. A lower dose of megestrol (20-40mg daily) can be an effective treatment for severe hot flashes associated with endocrine therapy [2] but whether this dose has anti-tumor activity is unknown. The PIONEER trial evaluated the potential anti-proliferative effect of low and high dose megestrol in combination with letrozole, relative to letrozole alone, using a short-term preoperative ‘window’ trial design assessing the direct effects of the trial treatment on tumor tissue before and after treatment. Methods: Eligible patients were post-menopausal women with histologically confirmed ER+ (Allred ≥ 3) HER2 negative breast cancer at least 10mm in size, with an ECOG performance status ≤ 2, planned for primary surgery or endocrine therapy. Enrolled patients were randomised 2:3:3 to Arm A: letrozole alone, Arm B: letrozole + lower-dose megestrol (40mg) or Arm C: letrozole + higher-dose megestrol (160mg). Treatment was given for 15 (13-19) days prior to surgery or end of treatment (EOT) core biopsy. The primary endpoint was change in tumor proliferation between baseline and EOT in Arm A vs (Arms B+C combined), measured by Ki67 immunohistochemistry (IHC). Secondary endpoints were comparison of Ki67 change in high versus low dose megestrol arms, absolute Ki67 at EOT, and change in tumor apoptosis (cleaved caspase 3 IHC), proliferation (Aurora Kinase A IHC), PR and androgen receptor expression. Exploratory analysis of ER chromatin binding (ChIP-Seq) was conducted on paired fresh-frozen samples from a subset of patients. Results: A total of 243 patients were randomised from July 2017 to October 2022 with recruitment paused for 3 months at onset of the COVID pandemic. 198 patients completed treatment and had evaluable tissue samples at baseline and EOT (Arm A: n = 51, Arm B: n = 74, Arm C: n = 73). Baseline mean Ki67 values were well balanced. Therapy was well tolerated and adverse events ≥ grade 3 were similarly rare across arms (A: 3.3%, B+C: 3.5%). The mean % reduction in Ki67 for each arm was: Arm A (letrozole): 71%, Arm B (letrozole + 40mg megestrol): 79%, Arm C (letrozole + 160mg megestrol): 80%. There was a statistically significantly greater reduction in Ki67 with megestrol combinations (B+C) versus letrozole alone (A) (P = 0.013). Analyses of secondary IHC endpoints and ER ChIP-Seq are ongoing and will be presented. Conclusion: Addition of the PR agonist megestrol enhanced the anti-proliferative effect of letrozole in this window-of opportunity trial. Megestrol combinations were well tolerated, and the anti-proliferative effect was observed in both low and high dose arms. These data support the potential use of low-dose megestrol as an inexpensive and well-tolerated means of improving aromatase inhibitor efficacy. Low dose megestrol can also ameliorate hot flashes and therefore might be a strategy to improve both treatment adherence and clinical outcomes for patients taking adjuvant endocrine therapy.

Abstract 1280: Role of the tumor microbiome in the lung adenocarcinoma immune microenvironment through multi meta-omics analysis

Abstract Lung cancer is the leading cause of death by cancer worldwide. The tumor microbiome has shed light on its role, influence, and modulation in cancer immunosurveillance, where the tumor-bacterial component emerges as a potential mediator for the antitumoral-immune response. Nevertheless, the complexities and functional mechanisms underlying this interaction remain elusive. Here, we outline how the tumor microbiota can impact the host´s immune response to lung adenocarcinoma (LUAD). We explored the microbiome within LUAD tumors and non-tumoral adjacent tissues (NAT) from Chilean patients. We used 10 paired (LUAD and NAT) fresh-frozen samples, 20 exclusively tumor fresh-frozen samples, and 40 exclusively tumor formalin-fixed paraffin-embedded samples. Using 16S rRNA gene sequencing, we assessed revealed variations in alpha diversity, with an intra-tumoral microbiome enriched in Gammaproteobacteria and Actinobacteria, particularly genera Pseudomonas and Corynebacterium in undifferentiated LUAD samples. Notably, a consistent depletion of Verrucomicrobiota with genus Akkermansia was evident in samples where cell differentiation was lost. Metaproteomics analysis revealed bacteria-associated peptides from Pseudomonas and Streptomyces enriched in the tumor, linked to Major facilitator superfamily (MFS) transporters and Glutathione S-transferase N-terminal domain-containing protein, both associated with transport activity and negatively correlated with cancer. The bacterial metabolic analysis uncovered 10 enriched microbial-associated metabolites in the tumor, highlighting adenosine and inosine, two known inducers of immunosuppression on T-cells in the tumor microenvironment. Host proteomics gene-ontology analysis highlighted an enrichment of proteins in the Interferon pathways. Concurrently, a downregulation of proteins like T-cell surface-glycoprotein CD8 and HLA-class I histocompatibility antigen was observed, linked to MHC protein complex binding function, and associated with immune evasion through diminished antigen presentation. Furthermore, upregulated proteins such as macrophage migration inhibition factor (MIF) and eIF-2-alpha kinase GCN2, known to stimulate cell proliferation, were identified. In summary, our multi-omics and bioinformatic analyses unveil a distinct intra-tumoral microbiome and microbe-derived metabolites could induce immune suppression, altering the metabolic profile in the LUAD tumor microenvironment and collectively contribute to tumor progression. Funding information: This work was supported by FONDECYT1231629 and ANID-Subdirección de capital humano/Doctorado Nacional/2023/21231386. Citation Format: Ivania Valdés, Alberto Martin, Eduardo Martínez, Daniel Carvajal Hausdorf, Erick Riquelme. Role of the tumor microbiome in the lung adenocarcinoma immune microenvironment through multi meta-omics analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1280.

Intraoperative Evaluation of Breast Tissues During Breast Cancer Operations Using the MasSpec Pen

Surgery with complete tumor resection remains the main treatment option for patients with breast cancer. Yet, current technologies are limited in providing accurate assessment of breast tissue in vivo, warranting development of new technologies for surgical guidance. To evaluate the performance of the MasSpec Pen for accurate intraoperative assessment of breast tissues and surgical margins based on metabolic and lipid information. In this diagnostic study conducted between February 23, 2017, and August 19, 2021, the mass spectrometry-based device was used to analyze healthy breast and invasive ductal carcinoma (IDC) banked tissue samples from adult patients undergoing breast surgery for ductal carcinomas or nonmalignant conditions. Fresh-frozen tissue samples and touch imprints were analyzed in a laboratory. Intraoperative in vivo and ex vivo breast tissue analyses were performed by surgical staff in operating rooms (ORs) within 2 different hospitals at the Texas Medical Center. Molecular data were used to build statistical classifiers. Prediction results of tissue analyses from classification models were compared with gross assessment, frozen section analysis, and/or final postoperative pathology to assess accuracy. All data acquired from the 143 banked tissue samples, including 79 healthy breast and 64 IDC tissues, were included in the statistical analysis. Data presented rich molecular profiles of healthy and IDC banked tissue samples, with significant changes in relative abundances observed for several metabolic species. Statistical classifiers yielded accuracies of 95.6%, 95.5%, and 90.6% for training, validation, and independent test sets, respectively. A total of 25 participants enrolled in the clinical, intraoperative study; all were female, and the median age was 58 years (IQR, 44-66 years). Intraoperative testing of the technology was successfully performed by surgical staff during 25 breast operations. Of 273 intraoperative analyses performed during 25 surgical cases, 147 analyses from 22 cases were subjected to statistical classification. Testing of the classifiers on 147 intraoperative mass spectra yielded 95.9% agreement with postoperative pathology results. The findings of this diagnostic study suggest that the mass spectrometry-based system could be clinically valuable to surgeons and patients by enabling fast molecular-based intraoperative assessment of in vivo and ex vivo breast tissue samples and surgical margins.

Abstract 909: Enhancing genomic analysis in cancer diagnostics: A machine learning approach for removing artifacts in FFPE specimens

Abstract Formalin-Fixed Paraffin-Embedded (FFPE) specimens, widely utilized in clinical cancer diagnostics, present significant challenges by introducing artifacts into genomic data. This study aimed to profile these FFPE-induced genomic alterations, with a particular focus on single-nucleotide variants (SNVs), small insertions and deletions (indels), and copy-number variations (CNVs), and to develop computational methods for filtering out such artifacts. Our primary focus was twofold: first, to comprehensively characterize the unique error profile of FFPE specimens observed through whole-genome sequencing (WGS), and second, to construct artifact classifiers and noise filters for SNV/indels and CNVs. We utilized machine learning (ML) and signal-processing techniques on a dataset of FFPE and matched fresh-frozen (FF) samples. The dataset of 52 FFPE-FF pairs were obtained from four different medical institutes and from various cancers including liver, breast, colon, stomach, and lung cancer, with varied FFPE archiving times. We also analyzed additional FFPE-only samples to refine our methods. Our methodology incorporated advanced computational approaches, including stacking ensemble, transfer learning, and wavelet transform, to enhance robustness and accuracy. The method's design was centered around the notion of not only achieving high performance in distinguishing true signals from FFPE-induced artifacts but also addressing the real-world challenges posed by the varying quality and conditions of clinical FFPE samples. In the analysis, we found peculiar patterns of FFPE-specific error profile, including well-known cytosine deamination and novel mutational signatures. The classifier, building on our findings, effectively differentiated true genomic variants from FFPE-induced artifacts for both SNVs and indels, demonstrating a sensitivity of 0.97, specificity of 0.87, and an F1 score of 0.94 for SNVs. For indels, it achieved a sensitivity of 0.91, specificity of 0.91, and an F1 score of 0.91. The CNV filter notably enhanced the signal-to-noise ratio (SNR) of CNV depth profiles, increasing it from 13dB to 17.5dB on average. Furthermore, we conducted evaluations on two critical measures in cancer and clinical genomics: homologous recombination deficiency (HRD) and tumor mutational burden (TMB), achieving post-filtering concordance rates of 0.99 for HRD—correctly identifying all 8 HRD-positive patients in our dataset—and 0.96 for SNV-based TMB and 0.87 for indel-based TMB. Additionally, a post hoc procedure for sensitive detection of cancer driver mutations resulted in concordance rates of 0.94 for SNVs, 0.91 for indels, and 0.95 for oncogene amplification. Taken together, our study advances FFPE WGS analysis in cancer diagnostics by effectively filtering artifacts and addressing challenges with older, degraded samples, enhancing clinical applicability. Citation Format: Joonoh Lim, Seongyeol Park, Won-Chul Lee, Ryul Kim, Sangmoon Lee, Jeong Seok Lee, Brian Baek-Lok Oh, Young Seok Ju. Enhancing genomic analysis in cancer diagnostics: A machine learning approach for removing artifacts in FFPE specimens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 909.

Abstract 5021: Circulating mutated and methylated tumor DNA detection for colorectal cancer diagnosis

Abstract Introduction: Detection of mutation and methylation patterns in liquid biopsies has emerged as a promising approach for screening early-stage cancers. We have developed a targeted next-generation sequencing (NGS)-based assay “OptiSeqTM Colorectal Cancer Detection Panel”, a combined platform for assessing mutation and methylation in both low-quantity (plasma cfDNA) and low-quality formalin-fixed paraffin-embedded (FFPE) tissue for colorectal cancer (CRC) detection. Methods: The OptiSeqTM Colorectal Cancer Detection Panel targets 442 SNVs and 434 CpG sites to detect circulating tumor DNA (ctDNA) in early-stage patients. With this panel, we profiled 6 early-stage and 6 metastatic CRC samples (matching cfDNA and FFPE) along with 2 primary colon specimens with adjacent normal tissue DNA. We also profiled 2 matching cfDNA and FFPE samples from precancerous adenomas (advanced adenomas (AA)) and 6 AA FFPE tissue DNA. In addition, we characterized the mutation and methylation pattern in 10 CRC fresh-frozen tissue DNA samples. For healthy individuals, we profiled 12 normal colon FFPE samples and 10 plasma cfDNA. The clinical performance for the CRC detection panel was calculated using AA, CRC, and cancer-free individuals. Results: For CRC early and metastatic matching cfDNA and FFPE samples, clinical samples testing showed that the CRC detection panel had a sensitivity of 100% (95% CI: 69.8-100.0) and specificity of 100% (95% CI: 81.5-100). For precancerous AA FFPE tissues, combined DNA mutation and methylation increased the CRC detection sensitivity to 100% (95% CI: 51.6-100.0) and specificity to 100% (95% CI: 61.8-100). More clinical samples testing is underway. Conclusion: We have developed the targeted NGS-based panel to detect clinically relevant mutation and methylation patterns and demonstrate its potential using the combined genetic and epigenetic markers making it a highly sensitive assay for early CRC diagnosis. Citation Format: Pushpinder Kaur Bains, Mikhail Kulak, Zhen Cui, Alisha Babu, Stella Tran, Aiguo Zhang, Michael Sha. Circulating mutated and methylated tumor DNA detection for colorectal cancer diagnosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5021.

Abstract 3406: Transcriptomic analysis reveals differentially expressed pathways in colon tumors of cancer patients with vs without obesity: Results from the ColoCare Study

Abstract Despite the rise of global obesity rates and obesity’s implication in increased colon cancer risk, the understanding of mechanisms underlying these associations and opportunities for interception are limited. This work leveraged transcriptomic data from colon tumors to identify pathways and biologically relevant functions that characterize the tumors among obese vs nonobese individuals. Fresh-frozen colon tumor samples were collected from 155 patients who underwent surgery without neoadjuvant treatment as part of the ColoCare Study at Huntsman Cancer Institute, Utah, and Heidelberg University Hospital, Germany. RNA was sequenced using the NovaSeq X. The DESeq2 R package identified differentially expressed genes stratified by body mass index (BMI) at diagnosis (&amp;gt;30 kg/m2 vs &amp;lt;30 kg/m2) adjusting for age, sex, study site, and tumor stage. Genes with padj &amp;lt; 0.2 were entered into Ingenuity Pathway Analysis (IPA) software for pathway and expression analyses. Significant pathways were identified using Fischer’s Exact Test as the probability of molecules’ association with canonical pathways due to chance. The analysis was also repeated testing a median BMI categorization of &amp;gt;27.7 kg/m2 vs &amp;lt;27.7 kg/m2 using padj &amp;lt; 0.1 for IPA entry. Patients were 49% female, 63±14 years old, 47% stage III with a mean baseline BMI of 28.8±6.0 kg/m2. In colon tumors of those with &amp;gt;BMI 30 kg/m2, 213 genes were differentially expressed compared to BMI &amp;lt;30 kg/m2. IPA identified five upregulated pathways (neurovascular coupling signaling, adrenergic receptor signaling, activation of N-methyl-D-aspartate receptors and postsynaptic events, response to elevated platelet cytosolic Ca2+, docosahexaenoic acid signaling) and one downregulated pathway (WNT/B-catenin signaling) in patients with vs without obesity (p &amp;lt;0.05). The top predicted functional pathways, based on activation z-scores, identified in expression analysis included significant activation in chromosomal instability and aberration, size of body, phosphorylation of L-tyrosine, protein kinase cascade, and cell death and survival categories among colon tumors in obese patients. Using a median BMI categorization, 458 genes and 35 pathways were differentially expressed in those with BMI &amp;gt; 27.7 kg/m2 vs &amp;lt; 27.7 kg/m2. Both BMI models had good agreement with 5 pathways consistently significantly (z-score &amp;gt; |2|) up- or down-regulated, including predicted downregulation of organismal death and increased body size and phosphorylation of L-tyrosine in the higher BMI group. Colon tumors from patients with a higher BMI had pathways associated with more aggressive tumors, such as increased chromosomal instability and decreased cell death. Our ongoing work investigates the role of the adipose-tissue tumor microenvironment among patients, and the potential for interception using parallel mouse models. Citation Format: Victoria M. Bandera, Tengda Lin, Caroline Himbert, Elaine M. Glenny, Aik Choon Tan, Jennifer Ose, Christy Warby, Olena Aksonova, Alessandro Carpanese, Chris Stubben, David Nix, Kenneth Boucher, Peter Schirmacher, Ildiko Strehli, Jolanta Jedrzkiewicz, Lyen C. Huang, Jessica N. Cohan, Alexander Brobeil, Martin A. Schneider, Christoph Kahlert, Erin M. Siegel, Adetunji T. Toriola, David Shibata, Christopher I. Li, Jane C. Figueiredo, Biljana Gigic, Jatin Roper, Stephen Hursting, Cornelia M. Ulrich. Transcriptomic analysis reveals differentially expressed pathways in colon tumors of cancer patients with vs without obesity: Results from the ColoCare Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3406.

Abstract 314: Fixative eXchange (FX)-seq reveals single nucleus transcriptional landscapes of archived clinical cancer FFPE specimens

Abstract The wide availability of FFPE tissues stored in hospitals and biobanks could potentially be an invaluable resource to gain insights for improved medical treatment towards precision medicine by combining genomic and transcriptomic data with pathological annotations and medical records. Nevertheless, the majority of current single-cell sequencing methods depend on fresh or fresh-frozen samples to generate high-quality transcriptome data due to the limited reverse transcription (RT) yields in FFPE samples. Consequently, single-cell level transcriptomic studies of FFPE samples have been a longstanding challenge. Here, we present Fixative-eXchange (FX)-seq, a highly scalable snRNA-seq method for heavily paraformaldehyde (PFA)-fixed and/or FFPE samples. We successfully analyzed a total of nearly 320k nuclei from various samples, including PFA-fixed tissue, FFPE blocks, FFPE and hematoxylin and eosin (H&amp;E)-stained sections from mouse brain and human clinical cancer specimens. In a human gastrointestinal stromal tumor (GIST) FFPE sample, we observed rare transcriptomic transitions toward increased epigenetic modifications affected by acquired resistance in response to prolonged imatinib treatment. Furthermore, in an archived human colorectal cancer (CRC) FFPE sample, spatially-contextualized FX-seq with pathologist annotation distinguishes tumor cells from epithelial progenitors along with identification of the tumor microenvironment (TME) such as cancer-associated fibroblasts (CAFs). We then proceeded to investigate transcriptional programs associated with drug resistance and lack of response in immunotherapy observed in CRC patients. With a hypothesis-driven curation, we compared transcription profiles at the single-nucleus level observed in MSS and MSI-H CRC patients from archived FFPE blocks and found distinctive transcriptional profiles from each group. Overall, FX-seq holds promise for clinical research, precision medicine, biomarker discovery, and molecular diagnosis using archived clinical FFPE specimens. Citation Format: Han-Eol Park, Yu Tak Lee, Jaewon Lee, Junsuk Lee, Hyelin Ji, Young-Lan Song, Yoon Dae Han, Hyunki Kim, Chang Ho Sohn. Fixative eXchange (FX)-seq reveals single nucleus transcriptional landscapes of archived clinical cancer FFPE specimens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 314.